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Generalised phrase structure grammars (GPSG's) appear to offer a means by which the syntactic properties of natural languages may be very concisely described. The main reason for this is that the GPSG framework allows you to state a variety of meta-grammatical rules which generate new rules from old ones, so that you can specify rules with a wide variety of realisations via a very small number of explicit statements. Unfortunately, trying to analyse a piece of text in terms of such rules is a very awkward task, as even a small set of GPSG statements will generate a large number of underlying rules.This paper discusses some of the difficulties of parsing with GPSG's, and presents a fairly straightforward bottom-up parser for them. This parser is, in itself, no more than adequate - all its components are implemented quite efficiently, but there is nothing tremendously clever about how it searches the space of possible rules to find an analysis of the text it is working on. Its power comes from the fact that it learns from experience: not new rules, but how to recognise realisations of complex combinations of its existing rules. The improvement in the system's performance after even a few trials is dramatic. This is brought about by a mechanism for recording the analysis of text fragments. Such recordings may be used very effectively to guide the subsequent analysis of similar pieces of text. Given such guidance it becomes possible to deal even with text containing unknown or ambiguous words with very little search.

Effective parsing with generalised phrase structure grammar